The Data is in the Details: Your Guide to Hotel Performance Analytics

Amanda McDowell
Amanda McDowell
Updated
February 20, 2025
/
Published
February 20, 2025
The Data is in the Details: Your Guide to Hotel Performance Analytics

Your hotel already collects a wealth of data. Information about who’s booking, your peak times and what’s driving the most revenue is at your fingertips — but how do you utilize it all?

That’s where hotel data analytics come in. From improving operational efficiency to enhancing guest experiences, leveraging the data insights you’re already collecting lets you work smarter (not harder!) and run a better hotel business.

So let’s take a look at how to make the most of your information. In this article, we’ll cover:

     
  • Key elements of hospitality data analytics
  •  
  • The data intelligence your hotel already collects
  •  
  • How data analysis improves the guest experience

What Are Hospitality Data Analytics?

In hospitality, data analytics involves gathering and analyzing information on customer behavior, booking trends, revenue streams and more to make smarter, data-driven decisions for managing your hotel.  

By monitoring key metrics, you gain deeper insights into your guests — understanding their preferences and identifying which offerings provide the most value. This not only helps increase revenue but also improves the overall guest experience.  

With advancements in AI, these analytics are becoming more precise and powerful, delivering detailed insights without adding to the workload for hoteliers.

What Data Does My Hotel Have?

Types of Data Hotel Tech Collects

Hotel operations are largely digital. That means data is always being collected. It’s just a matter of understanding what you have and how to use it.

For example, your property management system collects operational data points about the efficiency of your staff and your revenue management system provides insights into booking trends. And if you’re using a guest management system, you’ll know what upsells are the most popular, how satisfied guests are with their stay and insights into what conversations your staff is having with guests.

Types of Data Your Hotel Tech Collects

Property Management System

Revenue Management System

Guest Management System

  • Room inventory

  • Average length of stay

  • Historical reservations

  • Most popular room type

  • Overall profits and losses

  • Average cost of stay

  • Historical cashflow

  • Most profitable room type

  • Most popular upsells

  • Average message response time

  • Common check-in and checkout times

  • Guest ratings for specific parts of their stay

  • Average digital tips generated

A Quick Guide to the Types of Hotel Data Analytics

Data Analytics Terms to Note

Descriptive Analytics

Diagnostic Analytics

Predictive Analytics

Prescriptive Analytics

Real-Time Analytics

Looking at historical data like:

  • Past booking volume

  • Average length of stay (ALoS)

  • Common room types

Understanding the why behind data trends:

  • Connecting booking volume to special events

  • Sorting ALoS into guest segments

  • Attaching traveler personas to room types

Putting diagnostics into practice by:

  • Anticipating booking volume for upcoming events

  • Making predictions on occupancy based on ALoS

  • Understanding which type of traveler is likely to book and when

Recommending a course of action based on past events:

  • Raising prices when more bookings are anticipated

  • Offering promotions to get the ALoS to be profitable

  • Catering offerings to the type of traveler you anticipate

Monitoring data in real-time to make changes quickly:

  • Adjusting prices during high-volume booking days

  • Updating your length-based promotions in real-time

  • Turning add-on offerings on and off based on demand

Types of Hotel Data Analytics

Analytics Type

What It Does

Hospitality Example

Descriptive Analytics

Looks at past data to identify trends.

A hotel reviews last summer’s occupancy rates to plan for the upcoming season.

Diagnostic Analytics

Explains why something happened.

A resort discovers a booking spike was caused by a nearby music festival.

Predictive Analytics

Forecasts future trends based on past data.

A city hotel predicts a post-holiday dip and offers business traveler discounts.

Prescriptive Analytics

Recommends actions based on predicted outcomes.

A family resort launches a kids-stay-free promo before spring break to boost bookings.

Real-Time Analytics

Monitors live data for instant decision-making.

A mobile checkout system alerts housekeeping to prioritize room turnovers.

Hotels have access to a wealth of data—but how can you turn that data into actionable insights? That’s where hotel data analysis comes in.

While "data analytics" might sound intimidating, it doesn’t have to be. By getting familiar with a few key terms and methods, you’ll quickly feel more confident diving into the conversation. To help, we’ve rounded up some essential data analytics terms every hotelier should know.

Descriptive Analytics

Descriptive analytics examines historical data to understand past trends. This includes insights like past booking volume, average length of stay, and the most popular room types.

Example in hospitality: A hotel chain reviews last year’s occupancy rates and discovers that weekends in June had the highest demand. This insight helps them plan staffing and inventory for the upcoming summer season.

Diagnostic Analytics

Diagnostic analytics digs into the "why" behind an event. If there’s a sudden spike or drop in bookings, this analysis can reveal contributing factors, such as local events or competitor pricing changes.

Example in hospitality: A beachfront resort sees a 30% increase in bookings for a specific weekend. Diagnostic analytics shows that a popular music festival was announced nearby, driving demand.

Predictive Analytics

Predictive analytics uses historical data to forecast future trends, often with AI-powered tools. Hoteliers leverage this to anticipate demand shifts and optimize pricing strategies.

Example in hospitality: A city hotel analyzes past data and predicts a dip in bookings after the holiday season. To counteract this, they launch a limited-time discount for business travelers.

Prescriptive Analytics

Prescriptive analytics goes beyond predictions by recommending specific actions to maximize results. It suggests strategies based on data-driven probabilities.

Example in hospitality: A family-friendly resort uses AI-driven prescriptive analytics to identify that bookings from parents spike before spring break. In response, they launch a targeted email campaign offering kids-stay-free promotions.

Real-Time Analytics

Real-time analytics tracks data as it happens, allowing for immediate adjustments. AI-powered tools can analyze guest behavior and make instant recommendations.

Example in hospitality: A hotel’s mobile checkout system detects a surge in departures and automatically alerts housekeeping to prioritize room turnovers, reducing wait times for guests.

Key KPIs for Hotel Data Analytics

Now that you know what data you already have, you can dig into the key performance indicators (KPIs) that guide savvy decision-making. These provide assessments on financial performance, guest satisfaction and operational efficiency:

Financial Performance KPIs

Guest Satisfaction KPIs

Operational Efficiency KPIs

10 Ways Hospitality Analytics Data Helps Hotels

10 Ways Hospitality Analytics Data Helps Hotels

Once you know what to measure, you can really start to dig in! Insights like which upsells to offer, how to price your rooms and how to schedule your staff are now at your fingertips. Here are ten ways to use this information:

     
  1. Optimize staff scheduling: Use occupancy rates and booking data to predict peak periods and adjust staffing levels accordingly, reducing inefficient scheduling while maintaining service quality.
  2.  
  3. Enhance housekeeping efficiency: Analyze guest check-in and check-out patterns to streamline housekeeping schedules to ensure rooms are cleaned as soon as guests depart.
  4.  
  5. Improve inventory management: Use data to track supply usage and forecast demand, preventing shortages and reducing excess inventory costs.
  6.  
  7. Refine pricing strategies: Leverage revenue insights and optimized pricing models to adjust room rates dynamically based on market demand, local events, historical data and competitor pricing.
  8.  
  9. Streamline maintenance operations: Implement predictive maintenance by analyzing equipment performance data to address potential issues before they cause disruptions.
  10.  
  11. Increase marketing effectiveness: Utilize guest insights and targeted marketing campaigns to reach the right guests with personalized offers, boosting bookings and guest loyalty.
  12.  
  13. Forecast demand outlook: Reflect on historical booking data to forecast the future of booking demand to better plan for staffing, inventory and overall guest volume at different times.
  14.  
  15. Drive sustainable initiatives: Consider the data on energy consumption at your hotel and identify which initiatives would have the most impact.
  16.  
  17. Improve guest experiences: Use guest behavior data and booking patterns to personalize services, leading to higher satisfaction and repeat business.
  18.  
  19. Create custom upsells: Gain guest insights and use them to inform the type of upsells you offer, increasing revenue and personalization for guests.

Real-World Examples: Putting Data Into Action

Now that you know what data you have and how it can be used, let’s look at some ideas for how we can put it into practice.

Enhance the Guest Experience

Anticipate guest preferences

Guest data goes beyond names and birthdays. With a guest management system, you can collect information about guest behaviors and preferences and use AI to anticipate their needs automatically. For example, if you know a repeat guest prefers to check in early, adding an early check-in offer automatically adds a personalized touch to their registration flow.

Customize add-on offers

Using a dynamic upselling tool creates an opportunity to tailor every add-on offer to each guest type. Know a guest is visiting your oceanfront hotel with kids? Offer rentals that will help them have a blast at the beach! And for that couple celebrating something special? An offer for tableside champagne is sure to delight.

Resolve issues with ease

No matter how prepared you are, it’s inevitable that a guest will have an issue with something at some point—but how you handle it is what can turn their experience around! Keeping up with real-time analytics (like how fast service calls are answered) highlights where service may be falling short.

Optimize Hotel Operations

Implement predictive analytics

No one can tell the future, but predictive analytics can come close when they’re done right! For example, you can use this type of information to maximize your booking revenue if a music festival is coming to town or scale down your restaurant scheduling if a day is predicted to be slow.

Effectively manage maintenance

Hotel equipment works to keep everything running smoothly…until it doesn’t. Being surprised by a broken AC unit or a faulty pool pump is no way to spend a day. Implement a prescriptive analytics plan powered by machine learning to identify potential problems before they happen.

Create eco-friendly initiatives

By understanding your energy consumption, you can better identify places where you’re able to save. Say you notice that you’re using a lot of paper for registration cards—going digital can help you save money and increase your eco-friendly operations.

Generate More Revenue

Understand booking patterns

When you know the history behind booking patterns, pricing your rooms becomes a much easier process. Dynamically adjusting pricing to maximize revenue during busy periods and lowering costs to encourage bookings during slow times? Data lets you do it!

Get granular with marketing

You probably have a few different traveler personas you think of when designing your offers, and targeted marketing gives you data to work with. Making use of landing page A/B tests and targeting ads to your ideal guest gives you real statistics to guide your next promotion.

Strategically offer upsells

You can’t offer everything at your property, but you can offer the things that your ideal guest will appreciate. With the data from what add-ons are most popular, you can consider what new things might be worth adding and eliminate others from your inventory.

Your Security Checklist for Managing Hospitality Data

Hotel Data Security Checklist

On-Site

DigitalOnline

Operations

  • Implement strong security protocols for all data gathered

  • Regularly update all the software your hotel uses

  • Conduct regular staff training sessions focused on security

  • Encrypt pieces of sensitive information (credit card numbers, social security numbers, etc.)

  • Use role-based access for each staff member

  • Create an incident response plan

  • Enforce strong password policies

  • Map the guest journey to understand the flow of guest data and access

  • Use strong Wi-Fi network encryption

  • Set up firewalls and intrusion detection systems

  • Back up data regularly

  • Monitor network traffic to flag anything suspicious

  • Be sure your payment processor is PCI-compliant

  • Implement regular security measure audits

  • Back up data regularly

  • Communicate how data is collected, stored and used through a privacy policy

A conversation about gathering data isn’t complete without discussing data security. As with any type of business, hotels must implement secure ways of gathering and storing data and ensure they comply with their country’s rules and regulations.

Data breaches are serious business. Not only does the average hospitality industry data breach cost over $3 million, but it also leads to a damaged reputation that can have long-lasting impacts on revenue. Fortunately, there are plenty of steps hotels can take to protect the data they’ve collected on-site, online and through operations.

Protecting data on-site

     
  • Implement strong security protocols for all data gathered
  •  
  • Regularly update all the software your hotel uses
  •  
  • Conduct regular staff training sessions focused on security
  •  
  • Encrypt pieces of sensitive information (credit card numbers, social security numbers, etc.)
  •  
  • Use role-based access for each staff member
  •  
  • Create an incident response plan
  •  
  • Enforce strong password policies

Protecting data online

     
  • Map the guest journey to understand the flow of guest data and access
  •  
  • Use strong Wi-Fi network encryption
  •  
  • Set up firewalls and intrusion detection systems
  •  
  • Back up data regularly
  •  
  • Monitor network traffic to flag anything suspicious

Protecting data with operations

     
  • Be sure your payment processor is PCI-compliant
  •  
  • Implement regular security measure audits
  •  
  • Back up data regularly
  •  
  • Communicate how data is collected, stored and used through a privacy policy

Hospitality Analytics: Turning Data into Revenue

Using your hotel’s data to the fullest extent is more than just a nice-to-have! Modern hoteliers  are leveraging AI, data analytics and data security protocols now more than ever to stay ahead.

With the growing volume of data and the expanding capabilities of AI-powered tools, leveraging guest insights has never been more powerful. By mastering data analysis, hotels can unlock opportunities to optimize operations, boost revenue, elevate the guest experience, and safeguard their future.

Want to see how Canary can help you harness the power of data? Schedule a demo with us today.

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